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fft_CSV.py
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fft_CSV.py
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import scipy as sci
import pylab as plt
import numpy as np
import os
dir = os.getcwd()
os.chdir(dir)
data = np.genfromtxt('data2.csv', delimiter=',')
def fft():
rate=1000.00
t=np.arange(0,1,1/rate)
#t = np.zeros((0,data.shape[0]),np.float)
#t = data[:,0]
N=len(t)
s=np.sin(15*2*np.pi*t) + np.sin(25*2*np.pi*t+np.pi/4)+0.2*np.random.randn(t.size)
#s = np.zeros((0,data.shape[0]),np.float)
#s = data[:,1]
S=sci.fft(s)
"""
rate_np= 1/(data[1:2,0:1] - data[0:1,0:1])
for rate in rate_np:
f = 1/rate
print rate,f
freq_all=np.fft.fftfreq(N,f)
pidxs=np.where(freq_all>0)
freq= freq_all[pidxs]
"""
freq=rate*np.arange(0,(N/2))/N
n=len(freq)
power=abs(S[0:n])/N
#test = np.vstack([t,s])
test = np.vstack([freq,power])
test2 = np.transpose(test)
S2=S.copy()
S2[freq >26 ]=0
S2[(freq>16)&(freq<24)]=0
S2[freq <14]=0
main_sig=sci.ifft(S2)
np.savetxt("data2.csv",test2,fmt="%.5f",delimiter=",")
plt.subplot(1,3,1),plt.plot(t,s)
plt.subplot(1,3,2),plt.plot(freq,power),plt.xlim(0,200)
plt.subplot(1,3,3),plt.plot(t,main_sig)
plt.show()
if __name__ == '__main__':
fft()